Increased deepwater drilling today requires that expensive drillstem testing operations be optimized by other technologies that provide dynamic information of the formations to be tested. Wireline conveyed interval pressure transient tests (IPTT) are becoming a common practice today for optimizing and designing these expensive tests.
Typically, prior to IPTT, there is limited amount of information available about the reservoir and fluids properties. The fluid property information that is known tends to be generally probabilistic. Optimum design of IPTT tests is a challenge in order to achieve a successful and reliable test. IPTT may be dependent on the noise and on observable flow regimes associated with the pressure buildups. The success and reliability of the tests are not only a function of gauge metrology, but also of the formation deliverability and geometry.
IPTT is typically performed using the formation tester tool that straddles an interval of the target reservoir rock and isolating the interval from the borehole hydraulic pressure. Such a test is illustrated in FIG. 1. The formation fluid from the straddled interval is flowed by using a downhole pump thereby creating a pressure drawdown, which is followed by a buildup. Pressure transient analysis of the acquired data is used to determine various reservoir properties, such as permeability, formation pressure, skin, productivity, etc. Also, IPTT can be configured in various hardware options, such as with or without observation probes, etc., to give additional data that can be used to increase the confidence in the interpretation.
Development of a radial flow regime is desirable for optimum IPTT analysis. Radial flow regime corresponds to a zero slope portion of the Bourdet derivative on the pressure-derivative plot. FIG. 2 illustrates a typical Bourdet flow regime plot. The time of onset and the value of the radial flow regime derivative are primarily dependent on the formation and fluid properties of the tested interval.
An unambiguous identification of the radial flow regime is desirable for getting unique values of critical properties such as permeability, skin, etc. Sometimes, however, no reliable radial flow regime can be identified which can be attributed to:                Formation and fluid properties of the tested interval in which radial flow regime may not initiate in reasonable time. See FIG. 3.        Noise in the pressure signal during buildups; especially in high permeability formation where the signal to noise ratio tends to be low because of flow rate limitations of formation testers. See FIG. 4 where noise in the derivative plot renders reliable identification of radial flow.        
As shown in FIG. 5(a), when the permeability is higher, the reservoir reacts faster, and the pressure derivative deviates quickly away from the unit slope storage line and attains the radial flow zero slope trend earlier. Also, the value of the radial flow derivative is inversely related to the permeability. Formation thickness has a similar effect on the pressure derivative as shown in FIG. 5(b). The change in viscosity of the fluid has an inverse effect on the pressure derivative. The ratio of the permeability thickness to fluid viscosity correlates strongly to the value of the radial flow derivative.
FIGS. 5(c) and 5(d) depict the effect of porosity and total compressibility respectively on the pressure derivative plot. It can be seen that these two parameters are weakly correlated to the value of the radial flow derivative and the time of onset of radial flow.
It can be inferred from the sensitivity plots of FIGS. 5(e) and 5(f) that well bore storage constant and skin influence the onset of the radial derivative significantly; however, they have little effect on the value of the radial flow derivative.
Overall there are several parameters that effect the development of various flow regimes on the pressure derivative. For an optimum IPTT design, the effect of these parameters and the expected noise on the pressure derivative should be quantified. Since petrophysical and fluids information available during the planning stage of the IPTT is limited and has certain associated uncertainties, defining and quantifying a holistic effect of these parameters on the development of flow regime is a challenge. Also, each of these parameters, along with the gauge metrology, influences the noise observed on the derivative plot, and quantification of this noise poses further challenges.
Generally, IPTT tests are designed by simulating the pressure response by considering few variations in the flow rate and formation properties. It is very cumbersome and time consuming to consider all the possible variations of the several parameters which influence the pressure derivative flow regimes and limits the scope of this methodology. Moreover, the generally-used methodology is very limited in proposing any mitigation measures to ensure optimum data acquisition during IPTT.